In today's highly competitive market, performance optimization has become an important factor in attaining competitiveness, profitability and increased customer satisfaction. Combined with the demand and regulatory push for sustainable products, it has become imperative to analyze and optimize systems performance over their lifecycle: from the design stage to the disposal stage (from cradle to grave) including end of life treatment such as reconditioning and reuse or recycle.

In this issue of the International Journal of Performability Engineering (IJPE), we bring out seven papers dealing with problems relating to the Design of Products, Systems and Services for Dependability and Sustainability. According to the Handbook of Performability Engineering (Ed. Krishna B. Misra, Springer Verlag, 2008), sustainability requirements should be addressed along with other factors such as quality, reliability, maintenance and safety, for optimum performance. The objective is to produce products, systems and services that have built in quality, reliability, maintainability and safety, and are produced through clean production and technologies that result in minimal pollution, require minimum raw materials and energy and safe to dispose of or reuse at the end of their lives.

The papers included in this issue have gone through a rigorous two-stage blind-review process by the guest-editors and reviewers selected from amongst the best experts in performability engineering. Our goal is to bring to the readership of IJPE some key papers that will kick-start a vibrant and fruitful stream of research and industry papers in the area of sustainability and dependability.

In the first paper titled “State of the Art on Dependability and Sustainability across the Sustainable Value Chain”, Navin Chari et al. review the most recent advances in sustainability and dependability throughout the value chain. They focus on dependability factors within the green supply chains, life cycle analyses, and EcoDesign methodologies. They then propose a new sustainable product life cycle framework to represent key lifetime stages of sustainable products covering the collection, remanufacturing, reuse, and end-of-life support service systems. A section is devoted to the important issues of upgrade, maintenance, and warranty models in remanufacturing They conclude their paper with a discussion of future research challenges in this field.

In the second paper of the issue, viz., Reliability Analysis and Optimal Mixture Strategy for a Lot composed of New and Reconditioned Systems, Diallo et al., introduce and study the shape and the behavior of the failure rate of a mixture of two populations of components with the same distribution but different ages. This type of mixture is encountered in industrial settings when new and reconditioned systems are mixed together in remanufacturing or for maintenance operations. The conditions under which such a mixture of increasing failure rate components can result in a population with modified bathtub-shaped failure rate are derived. Through an illustrative example, they show that cost-optimal mixture strategies can be derived when reconditioned parts are mixed with new ones in remanufacturing or maintenance.

In the third paper by A. Jodejko-Pietruczuk and M. Plewa, viz., Component Rejuvenation in Production with Reused Elements, the authors present several models to estimate the cost-effectiveness of strategies for the reuse of returned elements in the production of new products. Their models are built for two-component systems and show the impacts that the reliability and cost of each component has on the ultimate remanufacturing decisions.

The fourth paper by Renyan Jiang and Yang Guo develops a robust non-parametric method to estimate the failure intensity function based on the failure processes observed from a single system, or several independent and identical systems, in estimating failure intensity of a repairable system, to decide on its preventive maintenance or retirement. After examining a large number of real-world datasets published in the literature, the authors found that the intensity function of repairable systems is typically of a roller-coaster curve shape. Jiang and Guo also provide several examples of this type of failure pattern along with possible causes. The usefulness of this method for planning the preventive maintenance and determining the retirement time of repairable products is also illustrated. A section is entirely devoted to the significance of this method for sustainability.

The fifth paper by A. Canal Marques titled “Teaching Sustainability Design of Products to Engineering Students” presents the result of a real-life teaching experiment. In this experiment, engineering students were taught how to select materials in the design phase to sustainably cover all stages of the life cycle of these products. The results show the complexity and importance of proper selection of materials and processes for sustainability.

The sixth paper “Dependent Systems Reliability Estimation by Structural Reliability Approach” by E. Kostandyan and J. Sørensen develops a method for dependent systems reliability estimation, where the leading failure mechanism(s) is described based on physics of failure model(s). Dependency is considered for both statistical and failure effect correlations. The proposed method can be used for calibration of limit state functions based on the test data availability and can easily be extended for dependent systems reliability estimation with non-identical components. It can also be used in various decision-making problems such as remanufacturing, when reuse alternatives depend on the system’s residual lifetime.

The seventh and last paper by H. Aoudjit et al. titled “Replacement Scheduling of a Fleet of Hydroelectric Generators: A Case Study” presents a framework to determine optimal maintenance planning of a fleet of complex and independent systems. Their framework uses proportional hazard model to characterize the failure rates of components and the effects of the environmental conditions and the load levels. A nonlinear program is developed to minimize the fleet maintenance cost under age replacement policy of its components and a set of organizational and technical constraints. Lindo API and NOMAD are used to solve the nonlinear model. The framework is applied to set a preliminary plan to overhaul a fleet of 90 hydroelectric generators in 6 power plants over 50 years for Hydro-Quebec.

The Guest Editors would like to thank all the authors for their contributions, and the reviewers for their dedication and the timely feedback provided to contributing authors of this special issue. The Guest Editors would also like to thank Prof. Krishna B. Misra, the Editor-In-Chief of IJPE, who was very helpful in the editing process as well as being a great and continuing supporter of performability knowledge dissemination.

Daoud Ait-Kadi is currently a full professor at the mechanical engineering department and director of graduate studies in industrial engineering at Laval University in Canada. He received his Bachelor’s degree in mechanical engineering from Ecole Mohammadia d’Ingénieurs in 1973, a Master of Science in industrial engineering from Ecole Polytechnique de Montreal in 1980 and a Ph.D. in industrial engineering, operations research and computer science from Montreal University in 1985. His research interests include production and operations management, reliability engineering, maintenance management, life cycle engineering and reverse logistics and spare parts management. He has authored many papers published in IEEE Transactions on Reliability, Naval Research Logistics, IJPR, IJPE, RESS, EJPR, JQME. He coauthored a textbook on stochastic processes (2004), a Handbook of maintenance management and engineering (2009) and two other books on replacement strategies and reverse logistics. He is currently involved in many industrial projects in automotive, aerospace, telecommunications, forest products, electronics and food industries. He is a senior member of IEEE and IIE. He is also a resident member of Hassan II Academy of Sciences and Technology (Morocco). Email: Daoud.Aitkadi@gmc.ulaval.ca

Uday Venkatadri (Ph.D., P.Eng) is an Associate Professor and the Head of the Department of Industrial Engineering at Dalhousie University in Halifax, Nova Scotia. He has taught at Dalhousie University since July 2001. Before joining Dalhousie, he was a Lead Architect for supply chain planning products at Baan. He has also worked as a Research Associate at Université Laval in Québec City. He holds a Ph.D. in Industrial Engineering from Purdue University, a Master of Science degree in Industrial Engineering from Clemson University, and a Bachelor’s degree in Mechanical Engineering from IIT-BHU, Varanasi, India.

His research interests are in facilities planning, production planning and control, and supply chain management. He teaches courses in these areas as well as operations research, modeling of industrial systems, information systems, algorithms, and quality control. He has published in journals such as the International Journal of Advanced Manufacturing Technology, International Journal of Peformability Engineering, Production Planning and Control, International Journal of Production Economics, European Journal of Operations Research, IIE Transactions, International Journal of Production Research, Journal of Manufacturing Systems, and Management Science,. He is a senior member of the Institute of Industrial Engineers (IIE), a member of the Canadian Operational Research Society (CORS) and a member of Engineers Nova Scotia.

His current research has been focused on production systems design. He is interested in incorporating congestion effects in production planning as well as multi-objective supply chain network design. He is working on product placement strategies to improve warehouse operations and continues to work in facilities design including but not limited to the block layout problem, multi-objective facilities design, and recourse issues in stochastic and dynamic facility layout problems. Email: uday.venkatadri@dal.ca

Claver Diallo Ph.D., P.Eng, is an Associate Professor in the Department of Industrial Engineering at Dalhousie University. He received the B.Eng. (1995), M.A.Sc. (2005), and Ph.D. (2006) degrees in mechanical engineering from Université Laval, Québec, Canada. From 1996 to 1999, he worked as a Field Engineer for Schlumberger Oilfield Services. His research interests include maintenance and availability optimization; inventory control; sustainable design; life cycle engineering; and dependability engineering. Email: cd@dal.ca